The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap

作者：Jie Deng, Sirisha Tadimalla, Tyler Seibert, H. Michael Gach, Petra J. van Houdt, David A. Hormuth, Xun Jia, Jiaren Zou, Christopher C. Conlin, Muge Karaman, Junzhong Xu, Jill De Vis, Lise Wei, Anna Dornisch, Joseph Weygand, Yu-feng Wang, Daniela Thorwarth, Xiaohong Joe Zhou, John C Gore, Xiaoyu Jiang, Taeho Kim, Annette Haworth, Heiko Enderling, Caroline Chung, Thomas E Yankeelov · 发表于：Physics in Medicine and Biology · 年份：2026 · DOI：10.1088/1361-6560/ae5d80 · 研究领域：MRI in cancer diagnosis、Advanced Radiotherapy Techniques、Radiomics and Machine Learning in Medical Imaging

This roadmap provides a comprehensive framework for integrating diffusion-weighted imaging (DWI) into radiation therapy (RT), with an emphasis on its application in magnetic resonance imaging-guided radiotherapy and its potential for driving biological image-guided adaptive radiotherapy (ART). Developed through collaboration among experts in medical physics, magnetic resonance imaging science, and radiation oncology, the paper aims to bridge disciplinary gaps and foster a shared understanding across scientific, technical, and clinical domains. It benchmarks the current state of DWI in RT, identifies critical challenges, and highlights recent advancements in acquisition, reconstruction, biophysical modeling, quality assurance, clinical validation and translation, as well as emerging concepts. By outlining ongoing efforts and forecasting future developments, this roadmap supports the adoption of DWI as a quantitative imaging biomarker for personalized and ART in precision oncology.